Super-capacity energy storage black-start wind power prediction error control optimization method

The invention discloses a super-capacity energy storage black-start wind power prediction error control optimization method, and relates to the technical field of super-capacity energy storage black-start, and the method comprises the steps: collecting multi-modal data, carrying out the preprocessing of the multi-modal data, inputting the preprocessed multi-modal data into a multi-modal variational auto-encoder model, carrying out the data fusion, and carrying out the calculation of the prediction error of the super-capacity energy storage black-start wind power. Generating a unified feature representation; constructing a prediction model by using the fused data, and performing multi-scale time sequence analysis in combination with wavelet transform; constructing a twin network to perform similarity learning, inputting historical data sample pairs, outputting similarity scores, identifying similar wind conditions in historical data, and optimizing a prediction model; and establishing a hierarchical Bayesian m